Implantable medical device responsive to heart rate variability analysis

ABSTRACT

A method and apparatus for evaluating heart rate variability of the heart of a person in order to forecast a cardiac event. A cardiac stimulator receives heart beat signals from the heart and determines a measurement of heart rate variability based on statistical data derived from the heart beat signals and sensing data derived from a sensor. This measurement of heart rate variability is compared with previously stored heart rate variability zones defining normal and abnormal heart rate variability. These zones are modifiable after the occurrence of a cardiac event. Once a cardiac event is detected, a pathway is computed which extends from a generally normal heart rate variability condition to an abnormal heart rate variability condition. Subsequent measurements of heart rate variability are compared with this pathway. Selective therapy regimes are initiated depending on the measurement of heart rate variability.

CROSS REFERENCE TO RELATED APPLICATION

[0001] This application is a divisional application of Ser. No.08/570,727, filed Dec. 11, 1995, which is incorporated herein byreference.

BACKGROUND

[0002] Traditionally, human heartbeat was thought to be regulatedaccording to classical principles of homeostasis. Under this theory, thehuman physiological system operates in a manner which adjusts heart ratevariability to achieve a state of equilibrium. Clinicians, in fact,traditionally described the normal beat activity of the heart as a“regular or normal sinus rhythm.”

[0003] Modern views now depart from these traditional ideologies. Morerecent studies and research show that, even with healthy individuals,the heart does not beat with metronomic regularity. Rather, the heartexhibits beat-to-beat fluctuations which are far from equilibrium. SeeC. K. Peng, et. al, “Fractal Landscapes in Physiology & Medicine:Long-Range Correlations in DNA Sequences and Heart Rate Intervals” pp.55-65, appearing in Fractals in Biology and Medicine, by T. F.Nonnenmacher, et. al (Ed.) (1994). Electrocardiograms, for example, showthat an individual will exhibit a fluctuating or erratic heart ratevariability during both rest and sleep periods.

[0004] Beat-to-beat fluctuations which occur around a person's meanheart rate are known as heart rate variability. The fluctuations frombeat-to-beat are attributed, in part, to the nonlinear interactionbetween the sympathetic and parasympathetic branches of the involuntarynervous system. The sympathetic autonomic and parasympathetic autonomicnervous systems regulate, to some extent, the sinoatrial (SA) node andatrioventricular (AV) node of the heart and, thus, largely influence thecontrol of the heart rate. These two nervous systems operate somewhatreciprocally to effect changes in the heart rate. In this regard,parasympathetic stimulation decreases the firing rate of the pacingcells located in the sinus node of the heart. Sympathetic stimulation,on the other hand, increases this firing rate.

[0005] Most clinicians agree that the parasympathetic and sympatheticinputs to the SA node mediate low frequency heart rate fluctuations(i.e., generally below 0.15 Hz), whereas modulation of parasympatheticoutflow mediates higher frequency fluctuations. Studies have furthershown that a decrease in heart rate variability correlates with adecrease in parasympathetic nervous activity and an accompanied increasein sympathetic nervous activity. See J. Thomas Bigger, et. al,“Components of Heart Rate Variability Measured During Healing of AcuteMyocardial Infarction” American Journal of Cardiology, Vol. 61 (1988),pp.208-215. In a healthy, resting heart, for instance, theparasympathetic activity dominates to maintain the heart rate. However,in an unhealthy heart, for example one having heart disease, sympatheticactivity may more influence and control the heart rate.

[0006] Over the past several years, heart rate variability wasincreasingly recognized as a diagnostic and a prognostic indication ofthe cardiac health risks to which a person is susceptible. As a result,much research has been directed toward heart rate variability. Inparticular, clinicians have been investigating the possibility thatheart rate variability may provide important information to forecastimpending cardiac anomalies. One study, for example, verified that a lowstandard deviation of heart rate variability is a powerful prognosticindicator of sudden coronary death in patients recovering from acutemyocardial infarction. See Alberto Malliani, et. al, “Power SpectralAnalysis of Cardiovascular Variability in Patients at Risk for SuddenCardiac Death” Journal of Cardiovascular Electrophysiology, Vol. 5(1994), pp. 274-286.

[0007] Today, cardiologists generally are in accord that heart ratevariability does have a correlation to the present condition of aperson's heart rate or the future occurrence of an abnormal cardiacevent. In fact, numerous studies have been performed which demonstratethis correlation. For example, if the heart rate of a healthy individualis compared to the rate of a patient having congestive heart failure,distinct differences in the beat intervals will be observed. In thisregard, the healthy individual will exhibit more complex patterns offluctuation than the non-healthy individual.

[0008] Furthermore, studies specifically relate heart rate variabilityto death in cardiac patients. Diminished heart rate variability now isassociated with an increased risk for ventricular fibrillation andsudden cardiac death. One study concluded:

[0009] Heart rate variability is an independent predictor of death whenother known postinfarction risk variables (for example, prolonged leftventricular ejection fraction, ventricular arrhythmias, and clinicalvariables) are considered. Heart rate variability has a higherassociation with risk for death than other variables obtained by Holtermonitoring, (for example, mean heart rate and ventricular arrhythmias).Heart rate variability also appears to be a better predictor ofarrhythmia complications than prolongation of the ejection fraction.

[0010] See Conny M. A. van Ravenswaaij-Arts, et. al, Annals of InternalMedicine, Vol. 118 (1993), pp. 436-447.

[0011] As noted, clinicians use heart rate variability to predict theonset of sudden cardiac death. Although the exact cause of cardiac deathis not completely understood, most victims suffer from ventriculartachycardia that degenerates into ventricular fibrillation.Investigators have exhausted significant effort to predict the onset andtriggers for such ventricular tachyarrhythmias. Heart rate variabilityis one available predictive value. Recent studies in this field verifythat a decrease or increase in heart rate variability during the firstseveral weeks after an acute myocardial infarction may be used topredict subsequent mortality or ventricular rhythmic disorders. Onestudy examined approximately 800 patients who had survived an acutemyocardial infarction and concluded that patients with a heart ratevariability of less than 50 milliseconds had a 5.3 times highermortality rate than those patients with a heart rate variability of morethan 100 milliseconds. See Robert E. Kleiger, et. al, “Decreased HeartRate Variability and Its Association with Increased Mortality AfterAcute Myocardial Infarction” American Journal of Cardiology, Vol. 59(1987), pp. 256-262. Patients experiencing congestive heart failure andcoronary artery disease also exhibit a decrease in heart ratevariability. See Casolo G. et. al, “Decreased Spontaneous Heart RateVariability in Congestive Heart Failure,” American Journal ofCardiology, Vol. 64 (1989), pp. 1162-1167.

[0012] Even in healthy individuals having normal heart rate variability,the heart rate intervals generally have a circadian variation. Thiscircadian variation, however, may begin to become less pronounced andmore irregular several minutes to several hours before the onset of anabnormal cardiac event. Researchers, for example, have found that heartrate variability progressively decreases in the hours preceding theonset of arrhythmia. Monitoring heart rate variability in such instancesthus provides clinicians with a tool to forecast impending cardiacevents.

[0013] As one advantage, measurements of heart rate variability aregenerally non-invasive and may be reliably performed. A Holter monitoror electrodes affixed to the patient measure heart rate very accurately.The electrodes detect the heartbeat, usually the R-R interval, for aseries of beats. Thereafter, statistical data, such as mean, median, andstandard deviation, are computed and then used to forecast the onset ofa cardiac event. One known method for using heart rate variability is tocompare heart rate intervals recorded under normal heart rate conditionsto subsequent heart rate intervals. Deviations between the tworecordings then may be used as an indication of heart rate variabilityfluctuation. In one embodiment, a Holter monitor records R-R intervalswhile the patient exhibits normal or healthy heart rate variability. Analgorithm based on mean and standard deviation then computes a singleuser value which is stored in permanent memory. This user valuerepresents the patient's stress state during normal heart ratevariability conditions. Thereafter, the patient wears a wrist detectorwhich monitors the R-R intervals for discrete beat periods, for example100 beats. Once a beat period is complete, the wrist detector uses thealgorithm to compute the patient's present user value or present stressstate. This present user value is then compared to the permanentlystored user value which was previously recorded under normal heart rateconditions. Theoretically, this comparison reveals deviations fromnormal heart rate variability which, in turn, are a measure of thepatient's cardiac stress state. Large deviations between the two uservalues reflect large deviations in the autonomic nervous system balancebetween the sympathetic and parasympathetic activities. For example, ifthe presently recorded user value deviates from the permanently storeduser value more than 25%, the patient may be subject to an elevatedstress level with an accompanying abnormal heart rate variability.

[0014] One important disadvantage associated with methods and apparatusfor utilizing heart rate variability concerns the failure to provide amore intelligent algorithmic structure. Heart rate variabilityalgorithms typically first compute a present user value based on the R-Rintervals. Thereafter, this present user value is compared with apreviously stored user value and a deviation between the two iscomputed. The algorithmic structure itself, however, remains unchanged.Thus, when subsequent R-R intervals are received and new user valuescalculated, these values are again compared with the same permanentlystored user value. As such, the algorithm repeatedly uses the samethreshold parameters defining normal and abnormal heart ratevariability.

[0015] Another disadvantage associated with methods and apparatus forutilizing heart rate variability concerns the treatment of heart ratevariability data leading up to an abnormal cardiac event. Devicesmeasuring heart rate variability often have memories which operate on afirst-in-first-out basis. These types of memories hold the heart ratedata in sequence and discard the oldest data and save the newest,incoming data. The older data, however, may provide importantinformation regarding the onset of subsequent cardiac events.

SUMMARY

[0016] The present invention is addressed to a method and apparatus forevaluating heart rate variability of a person in order to recognize orforecast a cardiac event. Heart rate variability zones initially areestablished to define normal and abnormal cardiac sinus rhythm of theperson. Thereafter, these zones are automatically modified after theoccurrence or non-occurrence of a cardiac event. As such, the boundsdefining normal and abnormal heart rate variability specifically adaptto a person's physiological and cardiological conditions. Once a cardiacevent occurs, a pathway leading up to that event is stored. Patientheart rate variability is then compared to this pathway to determine there-occurrence of a cardiac event.

[0017] In the present invention, a microprocessor-based cardiacstimulator receives heart-beat signals from the heart. The cardiacstimulator computes time intervals occurring between successive heartbeats and then derives a measurement of heart rate variability fromepoch data for predetermined time periods. This epoch data may includeboth statistical data derived from the time intervals and sensing dataderived from patient sensors. The cardiac stimulator then comparesmeasurement of heart rate variability with previously stored heart ratevariability zones which define normal and abnormal heart ratevariability. If the measurement of heart rate variability is within thelimits of an abnormal heart rate variability zone then an appropriatetherapy regime is initiated. On the other hand, if the measurement ofheart rate variability is within a normal heart rate variability zone, atherapy regime is not initiated. However, when the measurement of heartrate variability is within a normal heart rate variability zone and theperson is nevertheless experiencing a cardiac event, then the abnormalheart rate variability zone is modified to include the measurement ofheart rate variability. As such, the definition of normal and abnormalheart rate variability changes to meet the cardiac requirements of aparticular individual.

[0018] Once a cardiac event occurs, a memory permanently stores thepresent epoch data and, additionally, a series of epoch data leading upto the event. Together, this series of epoch data forms a pathway from agenerally normal heart rate variability condition to an abnormal heartrate variability condition. This pathway aids in predicting theoccurrence of future cardiac events and in identifying the occurrence ofpresent cardiac events. In this regard, all measurements of heart ratevariability occurring after the cardiac event are compared with thepathway. This comparison reveals whether the person is againexperiencing conditions similar to those leading to the prior cardiacevent

[0019] As another advantage, the abnormal heart rate variability zonemay be divided into a plurality of abnormal subzones. Each of thesesubzones corresponds to a therapy regime for initiating further sensingor therapeutic vigilance. Further, the therapy regimes may have astructure with progressively higher degrees of aggressiveness andvigilance.

[0020] Additionally, selective activation of therapy regimes minimizesnon-essential energy consumptive and diagnostic activities and, thus,conserves power supply longevity.

[0021] The invention, accordingly, comprises the apparatus and methodpossessing the construction, combination of elements, and arrangement ofparts which are exemplified in the following detailed description. For afuller understanding of the nature and objects of the invention,reference should be made to the following detailed description taken inconnection with the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

[0022]FIG. 1 is a block diagram of an implantable cardiac pulsestimulator;

[0023]FIG. 2 is a flow diagram for specifying heart rate variabilityparameters;

[0024]FIG. 3 is a perspective view of heart rate variability zones;

[0025]FIG. 4 is a block diagram of a therapy regime;

[0026]FIG. 5 is a flow diagram for calculating epoch statistical data;

[0027]FIG. 6 is a flow diagram for calculating epoch sensing data;

[0028]FIG. 7 is a flow diagram for comparing epoch data with storedheart rate variability parameters;

[0029]FIG. 8 is a perspective view of modified heart rate variabilityzones;

[0030]FIG. 9 is a flow diagram for comparing current epoch data withstored epoch data; and

[0031]FIG. 10 is a perspective view of a series of epoch data locationsleading to a cardiac event.

DETAILED DESCRIPTION

[0032]FIG. 1 is a block diagram illustrating an implantable cardiacstimulator 10 for carrying out the teachings of the present invention.Stimulator 10 may be a pacemaker, defibrillator, or other implantablepulse generator. A microprocessor 12 provides control and computationalfacilities for stimulator 10. Microprocessor 12 has input/output portsconnected in a conventional manner via bidirectional bus 14 to memory16, an A-V interval timer 18, and a pacing interval timer 20. A-Vinterval timer 18 and pacing interval timer 20 have an output connectedindividually via lines 22 and 24, respectively, to a corresponding inputport of microprocessor 12.

[0033] A-V and pacing interval timers 18 and 20 may be external tomicroprocessor 12, as illustrated, or internal thereto. Additionally,these timers may be conventional up/down counters of the type that areinitially loaded with a count value and count up to or down from thevalue and output a roll-over bit upon completing the programmed count.The initial count value is loaded into A-V and pacing interval timers 18and 20 on bus 14. Respective roll-over bits are output to microprocessor12 on lines 22 and 24. Memory 16 preferably includes both ROM and RAM.Generally, ROM stores operating routines, and RAM stores programmableparameters and variables.

[0034] Microprocessor 12 preferably also has an input/output portconnected to a telemetry interface 26 via line 28. Stimulator 10, whenimplanted, is thus able to receive variable and control parameters froman external programmer and to send data to an external receiver ifdesired. As such, operating parameters stored within microprocessor 12may be selectively altered non-invasively. Many suitable telemetrysystems are known to those skilled in the art. U.S. Pat. No. 4,539,992by Calfee, et al., issued Sep. 10, 1985 and entitled “Method andApparatus for Communicating with Implanted Body Function Stimulator”describes an example of a telemetry system and encoding arrangement.

[0035] Control lines 30 and 32 connect microprocessor output ports toinputs of an atrial stimulus pulse generator 34 and a ventricularstimulus pulse generator 36, respectively. Pulse parameter data, such asamplitude, width, enable/disable, and pulse initiation codes transmit togenerators 34 and 36 via lines 30 and 32, respectively. In addition,control lines 38 and 40 connect microprocessor input ports to outputs ofan atrial sense amplifier 42 and a ventricular sense amplifier 44,respectively. Atrial sense amplifier 42 detects the occurrences ofP-waves, and ventricular sense amplifier 44 detects the occurrences ofR-waves.

[0036] The input of atrial sense amplifier 42 and the output of atrialstimulus pulse generator 34 connect to a first conductor 46 whichconnects to a first conventional type lead 48. An electricallyconductive pacing/sensing tip 52 is located at a distal end of lead 48.This pacing/sensing tip electrically connects to conductor 46 andconnects, for example, to heart 50 in right atrium 54.

[0037] The input of ventricular sense amplifier 44 and the output ofventricular stimulus pulse generator 36 connects to a second conductor56 which connects to a second conventional type lead 58. An electricallyconductive pacing/sensing tip 62 is located at a distal end of lead 58.This pacing/sensing tip electrically connects to conductor 56 andconnects, for example, to heart 50 in right ventricle 60. Leads 48 and58 may be inserted into heart 50 transvenously or in any other suitablemanner.

[0038] Conductors 46 and 56 conduct the stimulus pulses generated inatrial and ventricular stimulus pulse generators 34 and 36,respectively, to pacing/sensing tips 52 and 62. Pacing/sensing tips 52and 62 and corresponding conductors 46 and 56 also conduct sensedcardiac electrical signals in the heart to atrial and ventricular senseamplifiers 42 and 44.

[0039] Cardiac stimulator 10 also may serve as a defibrillator. In thisregard, microprocessor 12 controls a high voltage defibrillator circuit64. Two high voltage leads 66 and 68 connect to the heart with twoelectrodes 70 and 72. In the illustrated embodiment, epicardial patchelectrodes are diagrammatically represented; although, other electrodeconfigurations, such as endocardial electrodes or others known to thoseskilled in the art, may be used.

[0040] The input and output ports of microprocessor 12 also connect tovarious sensors 74 via a bidirectional control bus 76. Implantablecardiac stimulators often employ sensors or sensing capabilities.Sensors 74 may be a variety of different sensing devices which gatherinformation about the patient. These sensors, for example, may senseventilation, acceleration, activity, oxygen level, blood pressure,temperature, blood oxygenation, blood pH, impedance, adrenaline levels,or the like.

[0041] Those skilled in the art will recognize that the presentinvention may be used with various implantable devices, with stimulator10 in FIG. 1 illustrating an example of one such device. Other possibleimplantable devices, for example, may be directed solely or jointly totachycardias, bradycardias, or fibrillation, and, in this regard,comprise a defibrillator, a single or dual chamber pacer, orcombinations thereof. In addition, the method of the invention may beused in devices which do not stimulate the heart at all or devices whichare not implantable. Such devices, however, must be able to sense orrecord the cardiac wave-form in order to measure the beat-to-beatintervals of the heart. Measurement of this interval may be doneremotely from the heart, for example with electrodes placed on thepatient, or within the heart itself, for example, from either theatrium, ventricle, or both.

[0042] In order to obtain the beat-to-beat interval between successiveheart beats, signals from the heart communicate from electrodes to thecardiac stimulator or other such monitoring device. In FIG. 1, eithersensing tip 52 or sensing tip 62 detects the heart's signals. Once thesesignals are detected, they may be processed in various ways to acquirethe beat-to-beat intervals. U.S. Pat. No. 5,201,321 by Fulton, issuedApr. 13, 1993, and entitled “Method and Apparatus for DiagnosingVulnerability to Lethal Cardiac Arrhythmias” teaches a method andapparatus for receiving heart beat signals and then calculating thebeat-to-beat intervals. As an example, the signal received from theheart is digitized, and the output is provided to a peak detector whichis connected to a memory. The peak detector measures the timing of thepeak amplitude, such as the A-A, P-P, V-V, or R-R interval of the heartsignal (A-A interval is the time between successive atrialdepolarizations as measured from within the atrium; P-P interval is thetime between successive atrial depolarizations as measured on the bodyof the patient; V-V interval is the time between successive ventriculardepolarizations as measured from within the ventricle; and R-R intervalis the time between successive ventricular depolarizations as measuredon the body of the patient). The memory or recording device then storesthe timing of the successive intervals. The timing intervals usually aremeasured in units of time or in terms of the number of samples betweenbeats. The particular method or apparatus used to record thebeat-to-beat intervals is less critical, as long as these intervals areaccurately obtained.

[0043] Preferably, the beat-to-beat intervals are recorded duringpredetermined lengths of time or epochs. The epoch period typically willendure for several minutes, for example five minutes, or for a givennumber of heart beats, for example 100 to 1000 beats. The length of theepoch is programmable and may vary. Preferably, beat-to-beat intervalsare continuously recorded for successive epochs.

[0044] The overall operating method and algorithm of the presentinvention is illustrated in a discussion of the flow diagrams whichfollow. The flow diagrams represent the program structure under whichmicroprocessor 12 preferably operates. The program structure may bewritten in a low level computer language, such as assembly, and retainedin a memory within the microprocessor.

[0045] Looking first to FIG. 2, a program structure commences at begin100. As represented at block 102, conventional initialization proceduresare performed. These procedures may include setting all pointers,registers, and counters, and clearing specified memory locations. Epochstatistical data then is selected, as depicted in block 104. Thisstatistical data generally includes computational and statisticalalgorithms, variables, equations, and the like known to those ofordinary skill in the art. Typically, this statistical data will includeany combination of at least one of a measure of central tendency or ameasure of dispersion Additional examples of statistical variables andequations which may be calculated for an epoch period include: mean, MAD(mean absolute deviation), median, mode (most commonly occurring heartrate variability interval), amplitude of mode (percentage that modeoccurs), variation range (difference between highest and lowest heartrate variability interval), PNN50 (percentage of heart rate intervalshaving a duration longer than 50 ms), standard deviation, range, powerspectral density, and variance

[0046] In order to evaluate the heart rate variability of the patientand, in turn, forecast the patient's heart condition, sensing data maybe used in addition to statistical data. Looking now to block 106, epochsensor data is selected. Sensing data is derived from sensors orelectrodes which measure physiological conditions of the patient. Suchsensors may be directed toward sensing, for example: evoked QTintervals, respiration, stroke volume, central venous oxygen saturation,right ventricular pressure, blood pressure, muscle noise, acceleration,impedance, activity or motion, temperature, blood pH, and adrenaline. Anactivity sensor, for example, is capable of measuring the movement andmotion of the patient.

[0047] Any combination of statistical equations/algorithms and sensingdata may be utilized to evaluate heart rate variability. Statisticalequations, for example, may be used singly or incorporated into astatistical algorithm to produce statistical data for a given epoch.This statistical data, in turn, may be combined with sensing data.Together, the statistical and sensing data form the epoch data for agiven epoch.

[0048] Block 108 shows that heart rate variability zones andcorresponding therapy regimes are designated and then stored intomemory. The heart rate variability zones define normal and abnormalheart rate variability for the patient. FIG. 3 illustrates an exemplaryheart rate variability zone configuration generally at 120. Threeseparate axes define configuration 120. Mean value of M intervalsdefines the x-axis; PNN50 defines the y-axis; and patient activitydefines the z-axis. Within configuration 120, an abnormal heart ratevariability zone is shown generally at 122. A normal heart ratevariability zone 124 occurs outside the boundaries of abnormal zone 122.

[0049] A set of parameters defines the boundaries or limits of abnormalzone 122 and normal zone 124. These parameters include values or rangesof values for each of the three axes. Preferably, the parameters divideabnormal zone 122 into a plurality of heart rate variability sub zones.FIG. 3 shows abnormal zone 122 subdivided into six different subzones126-131, respectively. Separate and independent sets of parametersdefine each subzone 126-131. Each of the subzones corresponds to adifferent heart rate variability state, and the subzones may have ahierarchical format with respect to the level of abnormality of heartrate variability or with respect to the corresponding cardiac conditionof the patient. For example, subzone 126 may represent heart ratevariability conditions with a more heightened degree of alert thansubzone 129.

[0050] In FIG. 3, a somewhat rectangular configuration illustrates eachsubzone. It will be appreciated that these configurations are forillustrative purposes and will vary depending on the parameters whichdefine the bounds of the subzones. In addition, the configurationsgenerally will depend not only on the statistical and sensor dataselected to define the subzones but also on particular physiologicalconditions and requirements of an individual patient. In this regard,each patient undergoing heart rate variability analysis may require adifferent set of parameters defining each subzone 126-131. Further yet,the subzones may have a plurality of different parameters. In FIG. 3,three different parameters define abnormal zone 122. The number ofparameters may vary from one to more than four or five. A fourthparameter, for example, could be time of day. Configuration 120 depictsthree parameters and six subzones for illustration.

[0051] The parameters bounds or limits for each subzone may beestablished before heart rate variability analysis commences. Forexample, a doctor or clinician may assign specific numerical values foreach of the subzones based on the medical history of a patient.Alternatively, the patient may undergo monitoring to determine limitsfor abnormal and normal heart rate variability. A Holter monitor orother device used to record and store heart rate variability data maymonitor the heart rate variability of the patient. Thereafter, limitsfor each of the subzones may be calculated based on this data. Asanother alternative, the boundaries defining the subzones may be basedon an initial estimation and pre-programmed into memory.

[0052] Each subzone also has an associated therapy regime. The therapyregimes preferably have a hierarchical format with respect to the levelof abnormality of heart rate variability or with respect to thecorresponding cardiac condition of the patient. In this regard, a lesserdegree of aggressiveness may be associated with a subzone having a moreacceptable heart rate variability and a more aggressive therapy assignedto a subzone having more abnormal heart rate variability.

[0053]FIG. 4 illustrates an exemplary therapy regime generally at 150.In this figure, therapy regime 150 has eight different therapy levels152-159. Commencing then with the least aggressive regime, therapy level152 calls for the initiation of more energy expensive tests or dataacquiring procedures to better or more accurately assess the heartcondition of the patient. These procedures may include various forms ofadded vigilance, such as activating a sensor which senses ventilation,acceleration, impedance, activity or motion, oxygen, blood pressure,temperature, blood oxygenation, blood pH, or adrenaline. Further, theprocedures may include increasing the level of diagnostic datacollection, for example, waveform storage with increased sampling rate,increasing diagnostic biopotential channel bandwidth, increasingparameter recordings, and increasing signal processing. Further yet,additional statistical data may be calculated or additional statisticalalgorithms employed. This statistical data may be based on heart rateintervals stored during current or previous epochs. Additionally, theinitiation of completely non-invasive procedures are possible. Forexample, a warning or alarm may communicate to the patient, healthprovider, clinician, or a designated location. Such a warning, forexample, could communicate the patient's pending heart condition or,alternatively, alert a clinician of the patient's condition or need foradded attentiveness. Next, therapy level 153 calls for bradycardiapacing or antibradycardia pacing. If the heart rate variability weremore abnormal, a higher rate overdrive pacing would be implemented, asshown in therapy level 154. Level 155 illustrates antitachycardia pacingand would occur, for example, if the patient were experiencing atrialflutter or ventricular tachycardia. The next higher level 156 calls fora form of neural stimulation to stimulate vagal activity of the patient.Level 157 illustrates activation of a counteractive drug dose. A druginfusion pump could infuse drugs to the patient to counteract anyincreased adrenalin and act as a tranquilizer. As such, the drug wouldeffectively normalize heart rate variability. If the patient experiencesyet a more extreme cardiac condition, a cardioversion shock may beinitiated, as shown at level 158. An extreme level 159 calls foradministering a defibrillation shock if the patient exhibits even moreextreme cardiac conditions or exhibits extreme abnormal heart ratevariability.

[0054] Selective activation of therapy regime 150 saves energy and thusconserves power supply longevity. In this regard, a heightened degree ofvigilance generally is not initiated until the patient exhibits anabnormal heart rate variability. Once abnormal variability is detected,a therapy regime, such as shown in levels 152-159, is initiated.Possible regimes, as noted, include additional sensing, computing, orthe like. Since these regimes require power to initiate, selectiveactivation saves energy. Further, during periods of abnormal heart ratevariability, non-essential computational and diagnostic activityoccurring within the stimulator may be suspended, halted, or notcommenced in order to reduce potential sources of interference anddevote computational resources to monitoring and diagnosing heart ratevariability or a cardiac event. For example, if an abnormal heart ratevariability is detected, unnecessary reforming of a defibrillatorcapacitor may be stopped. Each therapy level 152-159 may correspond to adifferent heart rate variability subzone. For example, looking also toFIG. 3, subzone 126 may correspond with therapy level 152, while subzone131 corresponds with therapy level 159. It will be appreciated that FIG.4 illustrates an example of one therapy regime. However, alternativetherapy regimes may differ for individual patients and be tailored tomeet specific cardiac requirements.

[0055] Additionally, other types of heart rate measurement andevaluation schemes also are available. For example, time domain analysisor a frequency domain analysis are two common ways researchers use toexamine heart rate variability. In the time domain analysis, a graphtypically displays the R-R intervals as the number of beats occurringduring a specified time. As an example, ECG monitors may record andcalculate heart rate variability. In the frequency domain analysis, aFourier transform algorithm decomposes sequential R-R intervals into asum of sinusoidal functions. A graph typically displays the result ofthis algorithm and shows the amplitude of the patient's heart ratefluctuations at different oscillation frequencies. The frequency domainanalysis is particularly advantageous in some instances because certainfrequency bands within the spectral analysis are associated withautonomic nervous system control of sinus node period. See J. ThomasBigger, et al, “Frequency Domain Measures of Heart Period Variabilityand Mortality After Myocardial Infarction” Circulation, Vol. 85 (1992),pp. 164-171.

[0056] Looking now to FIG. 5, a program structure is shown forcalculating selected epoch statistical data. The program structurebegins at 170 and commences conventional initialization procedures at172. Next, as shown in block 174, measurement of successive heart beatsignals occurs. Then, as represented at 176, the beat-to-beat intervalsbetween heart beats of the patient is calculated. These intervalsrepresent the time period between successive beats. A memory stores theintervals, as shown in block 178. Next, a query is made at block 180 todetermine whether the beat-to-beat interval has a length of time greateror less than 50 ms. If the beat-to-beat interval is greater than orequal to 50 ms, then a counter is incremented at 182. If the interval isless than 50 ms, a counter is incremented at 184. The counters may be inthe microprocessor or control circuitry and count the number of timesduring a single epoch the beat-to-beat intervals are greater or lessthan 50 ms. At block 186, a query determines if the epoch period ended.If the epoch period has not ended, then the program structure returns toblock 174 and continues to measure intervals between successive heartbeats. If the epoch has ended, statistical data is calculated for theepoch, as shown at 188. The statistical data calculated at 188 iscalculated for the data collected during the epoch. As illustrated inFIG. 3, the statistical data may also include, for example, PNN50 andMean. Once the statistical data is calculated, it is stored into memory,as shown in block 190. In addition to storing the statistical data forthe current epoch, counts one and two, the timing of the intervals, andthe time of day also are stored. The program structure of FIG. 5repeats, as shown along line 192, and again begins to measure heart beatintervals and calculate statistical data for succeeding epoch periods.

[0057] Turning now to FIG. 6, a program structure commences selectedsensing of the patient and calculation of sensing data. The programstructure begins at 200 and initiates conventional initializationprocedures at 202. Next, as shown in block 204, selected sensors areinitiated and begin to collect information for the current epoch period.As noted, a variety of different sensing devices may sense and collectdata from the patient. FIG. 3 illustrates initiation of an acceleration,activity, or motion sensor. Next, a query is made at block 206 todetermine whether the epoch period has ended. If the epoch period hasnot ended, then the program structure returns to block 204 and continuesto collect information. If the epoch has ended, the program structureproceeds to block 208, and the sensors selected in block 204 calculatesensing data for the epoch. For example, activity signals receivedduring the epoch may be averaged to indicate a mean activity rate Asshown in block 210, memory stores the sensing data and the time of day.At the end of the epoch, the program structure of FIG. 6 repeats, asshown along line 212, and again begins to sense using the selectedsensors.

[0058] Looking now to FIG. 7, a program structure is shown for modifyingstored heart rate variability zones which were previously stored intomemory. The heart rate variability zones are automatically customized toadapt to an individual person's physiological and cardiologicalconditions. The program structure begins at 216 and then proceeds toblock 218 which specifies collecting epoch data and deriving ameasurement of heart rate variability. Epoch data, including sensing andstatistical data, is collected and calculated as described in connectionwith FIGS. 2, 5, and 6. The measurement of heart rate variability isderived from the epoch data. This measurement of variability representsa measure of the person's or subject's heart rate variability for agiven epoch period and includes all of the epoch data or selectedportions. Next, a query in block 220 is made as to whether the end ofthe epoch period is reached. If the answer is negative, then epoch datais continued to be collected. If the answer is affirmative, the programstructure continues to block 222 and a query is made whether presentmeasurement of heart rate variability is within an abnormal heart ratevariability zone. FIG. 3 illustrates this occurrence. As shown, threedifferent axes (mean M, PNN50, and activity) define abnormal heart ratevariability zone 122 and normal heart rate variability zone 124. Themeasurement of heart rate variability is compared with zones 122 and 124to determine the present cardiac condition and heart rate variability ofthe patient for the present epoch.

[0059] If the present measurement of heart rate variability is withinabnormal heart rate variability zone 122, then, as shown in block 224,corresponding therapy is initiated. For example, FIG. 3 shows a possiblelocation 226 within subzone 128. If, on the other hand, the presentmeasurement of heart rate variability is not within abnormal heart ratevariability zone 122, then the query of block 228 is presented. FIG. 3shows a possible location 230 within normal zone 124 and outside thebounds of abnormal zone 122.

[0060] Block 228 queries whether the stimulator or measuring device isdetecting any form of abnormal cardiac condition. For example thestimulator may be initiating a therapy, detecting a cardiac event, orwithin a heightened alarm, warning, or sensing condition. For example,the patient may be experiencing a degree of tachycardia, bradycardia,fibrillation, dysrhythmia, arrhythmia, or the like. If the answer toblock 228 is negative, then the program structure proceeds to block 232and the epoch data, including the measurement of heart rate variability,is temporarily saved into memory. If, however, the answer to block 228is an affirmative, then heart rate variability zone configuration 120 ofFIG. 3 is modified to include the measurement of heart rate variabilitycorresponding to the present epoch sensor and statistical data.Modification, for example, may include enlarging or shortening theboundaries of one or more of subzones 129-131. Memory then stores theepoch data and measurement of heart rate variability as shown in block236.

[0061]FIG. 3 illustrates a possible location 238 which is not initiallywithin abnormal zone 122. Thus, no therapy would be initiated due toheart rate variability data of the patient. However, if the stimulatoror measuring device concurrently detects an abnormal cardiac condition,the stimulator itself may initiate a therapy or heightened level ofvigilance. In this instance, the parameters of abnormal zone 122 changeto include the parameters of location 238. FIG. 8 illustrates thisoccurrence wherein the parameters of subzone 129 enlarge to includelocation 238. The modified heart rate variability zone configuration120′, including modified subzone 129′, is permanently stored intomemory. Subsequent measurements of heart rate variability are thencompared to modified configuration 120′.

[0062] Looking now to FIG. 9, a program structure is shown for comparingpresent epoch data with previously stored epoch data to determine theheart condition of the patient. The previously stored epoch datarepresents instances in which the patient experienced a cardiac event orsome form of abnormal cardiac condition. A comparison between thepresent epoch data and the stored epoch data then aids in predicting are-occurrence of the event.

[0063] The occurrence of a cardiac event signifies that the patient'sheart is experiencing a cardiac anomaly. Such an anomaly, for instance,may be recognized as an abnormal cardiac rhythm, as a cardiaccomplication, or as an indication of a possible impending abnormalcardiac condition. Examples of an anomaly would include arrhythmia,dysrhythmia, fibrillation, tachycardia, bradycardia, flutter, myocardialinfarction, heart disease or sickness, or the like.

[0064] The program structure begins at 250 and then proceeds to block252 which specifies collecting epoch data and deriving a measurement ofheart rate variability. FIGS. 2, 5, and 6 describe the collection andcalculation of epoch data. Next, a query in block 254 is made as towhether the end of the epoch period is reached. If the answer isnegative, then the program structure loops to block 252, and epoch datais continued to be collected. If the answer is affirmative, the programstructure continues to block 256 and a query is made as to whether acardiac event has occurred. If a cardiac event occurs, memory stores theepoch data as shown in block 258. FIG. 10 illustrates storage of thisepoch data.

[0065]FIG. 10 shows an exemplary heart rate variability zoneconfiguration 270 having mean AA value as the x-axis, MAD as the y-axis,and patient respiration as the z-axis. Two hypothetical epoch series areshown at 274 and 276, respectively. Epoch series 274 includes aplurality of measurements of heart rate variability shown at 278-282.Measurements 278-282 represent epoch data locations leading to a cardiacevent shown at measurement 282. Epoch series 276 illustrates a pluralityof measurements of heart rate variability 284-288 leading up to acardiac event represented at location 288. Each of the measurementsincludes all or part of the epoch data and other information collectedand stored during a corresponding epoch. Epoch series 274, for example,may have ended in a bradycardia event at location 282. Pathway 290represents an abnormal heart rate variability path or zone and is shownas a line leading to measurement 282. Epoch series 276 may have ended ina tachycardia event at measurement 288. A pathway 292 is shown as a lineleading to this measurement.

[0066] Each heart rate variability pathway 290 and 292 may be expandedto include an abnormal heart rate tolerance zone, shown at 294 and 296,respectively. Tolerance zones 294 and 296 serve to enlarge pathways 290and 292 and provide broader limits or boundaries defining the epochseries leading to the cardiac event. Preferably, the tolerance zonewould expand pathways 290 and 292 from about 10% to 20%.

[0067] Epoch series 274 and 276 may provide a predictable avenue throughwhich subsequent cardiac events occur. In this regard, individualpatients may experience numerous cardiac events over a given period oftime. Two or more of these events may have a preferred or common pathwayleading to a particular event. For example, two separate cardiac eventsmay start at different measurement locations but progress to or througha zone of commonality. The pathways, in fact, may partially or fullyoverlap. As such, the stored pathways may be compared with presentpathways to aid in forecasting future cardiac events or to aid inrecognizing the onset of a current event.

[0068] Additionally, cardiac events occur suddenly or develop over amore extended period of time. Once an event occurs, the present epochdata exhibiting that event is stored in permanent memory. In addition,prior epoch data also is permanently stored into memory. Thus, memorystores a series of epoch data once a cardiac event occurs. The amountand number of prior epoch data stored may depend on memory allocationavailability, on the length of epoch time, or on the compressibility ofthe data, for example. Preferably, about several hours of prior epochdata are stored after the occurrence of a cardiac event.

[0069] The time of day in which the epoch occurs also may be a factorwhen comparing a current epoch with a stored epoch series. Epoch datamay exhibit a circadian variation over a given time period. For example,when a person is sleeping, the mean heart rate, mean minute ventilation(i.e., an indication of the metabolic demand), and mean activity will belower, and PNN50 and mean absolute deviation will be relatively higher.When the person is awake and active, such as exercising, the mean heartrate, mean minute ventilation, and mean activity will be relativelyhigher, and the PNN50 and mean absolute deviation will be relativelylower.

[0070] As another factor, a smaller amount of variability exists athigher heart rates. For example, a person with a heart rate of 100 bpmtypically will have more sympathetic nerve activity inhibiting vagalaction. In this situation, the heart rate variability of the patientexpectedly is extremely low. If the heart rate were maintained at 100bpm and pacing used to effectuate heart rate variability, little effectmay result.

[0071] Turning back now to FIG. 9, as noted, if the answer to the queryin block 256 is positive, then the epoch data is permanently stored intomemory, as shown in block 258 and described in connection with FIG. 10.If the answer is negative, then a comparison is made between the currentmeasurement of heart rate variability and stored epoch series, as shownin block 300. Block 302 then queries whether the current measurement ofheart rate variability matches the stored epoch series. If no matchexists, then the epoch data is temporarily stored, as shown in block304. If a match does exist, then block 306 indicates an appropriatetherapy is initiated.

[0072]FIG. 10 illustrates the comparison between current measurement ofheart rate variability and stored epoch series. Epoch series 307 hasthree measurements of heart rate variability 308, 310, and 312. Twomeasurements or locations 308 and 310 are shown outside the boundariesor limits of either pathway 290 and tolerance zone 294 or pathway 292and tolerance zone 296. Thus, neither of these two measurements matchthe stored epoch series. However, measurement 312 is within theboundaries of tolerance zone 294. Thus, a match exists betweenmeasurement 312 and epoch series 274.

[0073] Any of a variety of therapy regimes may be initiated if thecurrent measurement of heart rate variability matches the stored epochseries. FIG. 4 shows alternate therapies. As one possibility, the sametherapy regime originally initiated during the occurrence of the storedepoch series also could be initiated. For example, since measurement 304in FIG. 10 is within the boundaries of tolerance zone 294, the sametherapy initiated with measurement 279 or 278 could be initiated.Therapy regimes with a conservative and less aggressive approach alsoare possible. In this instance, more energy expensive vigilance maysuffice. For example, additional sensors may be activated or a warningor alarm may be communicated. Alternatively, the aggressiveness of atherapy regime may depend on the potentially ensuing event. For example,pathway 274 may have led to a slow ventricular tachycardia which wasotherwise not fatal to the patient. Antitachycardia pacing may havesufficed to correct the arrhythmic event. A similar therapy regime couldbe employed.

[0074] Since certain changes may be made in the above-describedapparatus and method without departing from the scope of the inventionherein involved, all matter contained in the description or shown in theaccompanying drawings shall be interpreted as illustrative and not in alimiting sense.

What is claimed:
 1. A method for evaluating heart rate variability ofthe heart of a patient, comprising the steps of: receiving a pluralityof heart beat signals from said heart for each of a plurality of epochs;computing a measurement of heart rate variability for each of saidepochs; defining an abnormal heart rate variability zone to include afirst measurement of heart rate variability from a corresponding firstepoch if said heart exhibits a cardiac anomaly during said first epoch;and comparing said abnormal heart rate variability zone with saidmeasurements of heart rate variability occurring after said first epoch.2. The method of claim 1 further comprising the step of modifying saidabnormal heart rate variability zone to further include a series ofsuccessive measurements of heart rate variability occurring before andleading to said first epoch.
 3. The method of claim 2 further comprisingthe steps of: creating a pathway along said series of successivemeasurements; modifying said abnormal heart rate variability zone toinclude said pathway; and comparing said modified abnormal heart ratevariability zone with said measurements of heart rate variabilityoccurring after said first epoch.
 4. The method of claim 3 in which saidpathway is expanded to include a tolerance zone.
 5. The method of claim4 in which said tolerance zone expands said pathway about fifteenpercent.
 6. The method of claim 1 in which said heart beat signals forsaid first epoch and said first measurement of heart rate variabilityare stored in permanent memory if said heart of said patient exhibitssaid cardiac anomaly.
 7. The method of claim 1 further comprising thestep of modifying said abnormal heart rate variability zone if saidheart of said patient exhibits another cardiac anomaly after said firstepoch.
 8. The method of claim 1 in which said measurements of heart ratevariability occurring after said first epoch are stored in permanentmemory when said measurements of heart rate variability are within saidabnormal heart rate variability zone.
 9. The method of claim 1 furthercomprising the step of expanding said first measurement of heart ratevariability to include a tolerance zone.
 10. The method of claim 1 inwhich said cardiac anomaly is an abnormal fluctuation of sinus rhythm ofsaid heart beat signals.
 11. The method of claim 1 in which said cardiacanomaly is one of arrhythmia, dysrhythmia, fibrillation, tachycardia,bradycardia, flutter, myocardial infarction, and heart disease.
 12. Themethod of claim 1 in which said step of computing said measurement ofheart rate variability further comprises the step of computing one ofmean absolute deviation, standard deviation, measure of centraltendency, and range.
 13. A method for evaluating cardiac sinus rhythm ofa patient, comprising the steps of: defining an abnormal heart ratevariability zone for said patient; receiving a first series of heartbeat signals from the heart of said patient during a first time period;computing said heart beat signals into a first measurement of heart ratevariability; comparing said first measurement of heart rate variabilitywith said abnormal heart rate variability zone; and modifying saidabnormal heart rate variability zone to include said first measurementof heart rate variability if the heart of said patient exhibits acardiac anomaly during said first time period.
 14. The method of claim13 further comprising the steps of: receiving a second series of heartbeat signals from the heart of said patient during a second time periodoccurring after said first time period; computing said second heart beatsignals into a second measurement of heart rate variability; andcomparing said second measurement of heart rate variability with saidmodified abnormal heart rate variability zone if said patient exhibitssaid cardiac anomaly during said first time period, otherwise comparingsaid second measurement of heart rate variability with said abnormalheart rate variability zone.
 15. The method of claim 14 furthercomprising the step of further modifying said modified abnormal heartrate variability zone to include said second measurement of heart ratevariability if the heart of said patient exhibits another cardiacanomaly during said second time period.
 16. The method of claim 13further comprising the steps of: defining said abnormal heart ratevariability zone to include a plurality of abnormal heart ratevariability subzones; designating a therapy regime for each of saidsubzones; comparing said first measurement of heart rate variabilitywith each of said subzones; and initiating one of said therapy regimesif one of said subzones includes said first measurement of heart ratevariability.
 17. The method of claim 13 in which said first measurementof heart rate variability is derived from statistical data derived fromsaid heart beat signals and sensing data derived from sensormeasurements.
 18. The method of claim 17 in which: said statistical dataincludes one of a measure of central tendency and a measure ofdeviation; and said sensor measures one of: evoked QT intervals,respiration, stroke volume, central venous oxygen saturation, rightventricular pressure, blood pressure, impedance, muscle noise,acceleration, activity, temperature, blood pH, and adrenaline.
 19. Themethod of claim 13 in which said cardiac anomaly is an abnormalfluctuation of sinus rhythm of said heart beat signals.
 20. The methodof claim 13 further comprising the steps of: storing in memory saidabnormal heart rate variability zone; modifying said abnormal heart ratevariability zone to include said first measurement of heart ratevariability when said first measurement of heart rate variability isoutside limits of said abnormal heart rate variability zone; and storingin memory said modified abnormal heart rate variability zone.